Python数据框的置信区间

import pandas as pdimport numpy as npimport mathdf=pd.Dataframe({'Class': ['A1','A1','A1','A2','A3','A3'],       'Force': [50,150,100,120,140,160] },      columns=['Class', 'Force'])print(df)print('-'*30)stats = df.groupby(['Class'])['Force'].agg(['mean', 'count', 'std'])print(stats)print('-'*30)ci95_hi = []ci95_lo = []for i in stats.index:    m, c, s = stats.loc[i]    ci95_hi.append(m + 1.96*s/math.sqrt(c))    ci95_lo.append(m - 1.96*s/math.sqrt(c))stats['ci95_hi'] = ci95_histats['ci95_lo'] = ci95_loprint(stats)

输出是

  Class  Force0    A1     501    A1    1502    A1    1003    A2    1204    A3    1405    A3    160------------------------------       mean  count        stdClass  A1      100      3  50.000000A2      120      1        NaNA3      150      2  14.142136------------------------------       mean  count        std     ci95_hi     ci95_loClass    A1      100      3  50.000000  156.580326   43.419674A2      120      1        NaN         NaN         NaNA3      150      2  14.142136  169.600000  130.400000